Lifestyle Factors Research Articles

Exploring online public survey lifestyle datasets with statistical analysis, machine learning and semantic ontology

Lifestyle diseases significantly contribute to the global health burden, with lifestyle factors playing a crucial role in the development of depression. The COVID-19 pandemic has intensified many determinants of depression. This study aimed to identify lifestyle and demographic factors associated with depression symptoms among Indians during the pandemic, focusing on a sample from Kolkata, India. An online public survey was conducted, gathering data from 1,834 participants (with 1,767 retained post-cleaning) over three months via social media and email. The survey consisted of 44 questions and was distributed anonymously to ensure privacy. Data were analyzed using statistical methods and machine learning, with principal component analysis (PCA) and analysis of variance (ANOVA) employed for feature selection. K-means clustering divided the pre-processed dataset into five clusters, and a support vector machine (SVM) with a linear kernel achieved 96% accuracy in a multi-class classification problem. The Local Interpretable Model-agnostic Explanations (LIME) algorithm provided local explanations for the SVM model predictions. Additionally, an OWL (web ontology language) ontology facilitated the semantic representation and reasoning of the survey data. The study highlighted a pipeline for collecting, analyzing, and representing data from online public surveys during the pandemic. The identified factors were correlated with depressive symptoms, illustrating the significant influence of lifestyle and demographic variables on mental health. The online survey method proved advantageous for data collection, visualization, and cost-effectiveness while maintaining anonymity and reducing bias. Challenges included reaching the target population, addressing language barriers, ensuring digital literacy, and mitigating dishonest responses and sampling errors. In conclusion, lifestyle and demographic factors significantly impact depression during the COVID-19 pandemic. The study’s methodology offers valuable insights into addressing mental health challenges through scalable online surveys, aiding in the understanding and mitigation of depression risk factors.

Brighter nights and darker days predict higher mortality risk: A prospective analysis of personal light exposure in >88,000 individuals

Light enhances or disrupts circadian rhythms, depending on the timing of exposure. Circadian disruption contributes to poor health outcomes that increase mortality risk. Whether personal light exposure predicts mortality risk has not been established. We therefore investigated whether personal day and night light, and light patterns that disrupt circadian rhythms, predicted mortality risk. UK Biobank participants (N = 88,905, 62.4 ± 7.8 y, 57% female) wore light sensors for 1 wk. Day and night light exposures were defined by factor analysis of 24-h light profiles. A computational model of the human circadian pacemaker was applied to model circadian amplitude and phase from light data. Cause-specific mortality was recorded in 3,750 participants across a mean (±SD) follow-up period of 8.0 ± 1.0 y. Individuals with brighter day light had incrementally lower all-cause mortality risk (adjusted-HR ranges: 0.84 to 0.90 [50 to 70th light exposure percentiles], 0.74 to 0.84 [70 to 90th], and 0.66 to 0.83 [90 to 100th]), and those with brighter night light had incrementally higher all-cause mortality risk (aHR ranges: 1.15 to 1.18 [70 to 90th], and 1.21 to 1.34 [90 to 100th]), compared to individuals in darker environments (0 to 50th percentiles). Individuals with lower circadian amplitude (aHR range: 0.90 to 0.96 per SD), earlier circadian phase (aHR range: 1.16 to 1.30), or later circadian phase (aHR range: 1.13 to 1.20) had higher all-cause mortality risks. Day light, night light, and circadian amplitude predicted cardiometabolic mortality, with larger hazard ratios than for mortality by other causes. Findings were robust to adjustment for age, sex, ethnicity, photoperiod, and sociodemographic and lifestyle factors. Minimizing night light, maximizing day light, and keeping regular light-dark patterns that enhance circadian rhythms may promote cardiometabolic health and longevity.

Frailty Indicator over the Adult Life Cycle as a Predictor of Healthcare Expenditure and Mortality in the Short to Midterm.

Assessing frailty from middle age onward offers valuable insights into predicting healthcare expenditures throughout the life cycle. This paper examines the use of physical frailty as an indicator of healthcare demand across all age groups. The originality of this work lies in extending the analysis of frailty indicators beyond the typical focus on individuals under 50 years old to include those in mid-life and older. For this study, we used a database where frailty was measured in 2012 in a sample of individuals aged 15 to over 90. These individuals were tracked for their healthcare expenditures from 2012 to 2016. Among the sample of 6928 individuals, frailty in 2012 resulted in a statistically significant increase in costs at the 5% level for the population aged 15 to 65. We applied multilevel linear regression models with year fixed effects, controlling for demographic factors, education level, precarity, social dimensions, lifestyle factors (e.g., vegetable consumption), physical activity, emotional well-being, and medical history. A Hausman test was conducted to validate the model choice. For mortality rate analysis, Cox models were used. Our findings demonstrate that physical frailty provides valuable information for understanding its impact on healthcare expenditure. The effect of frailty on mortality is particularly significant for the elderly population. Moreover, frailty is a predictor of healthcare costs not only in older adults but also across the entire life cycle.

Predicting stroke occurrences: a stacked machine learning approach with feature selection and data preprocessing

Stroke prediction remains a critical area of research in healthcare, aiming to enhance early intervention and patient care strategies. This study investigates the efficacy of machine learning techniques, particularly principal component analysis (PCA) and a stacking ensemble method, for predicting stroke occurrences based on demographic, clinical, and lifestyle factors. We systematically varied PCA components and implemented a stacking model comprising random forest, decision tree, and K-nearest neighbors (KNN).Our findings demonstrate that setting PCA components to 16 optimally enhanced predictive accuracy, achieving a remarkable 98.6% accuracy in stroke prediction. Evaluation metrics underscored the robustness of our approach in handling class imbalance and improving model performance, also comparative analyses against traditional machine learning algorithms such as SVM, logistic regression, and Naive Bayes highlighted the superiority of our proposed method.

Machine learning-based personalized composite score dissects risk and protective factors for cognitive and motor function in older participants.

With age, sensory, cognitive, and motor abilities decline, and the risk for neurodegenerative disorders increases. These impairments influence the quality of life and increase the need for care, thus putting a high burden on society, the economy, and the healthcare system. Therefore, it is important to identify factors that influence healthy aging, particularly ones that are potentially modifiable through lifestyle choices. However, large-scale studies investigating the influence of multi-modal factors on a global description of healthy aging measured by multiple clinical assessments are sparse. We propose a machine learning model that simultaneously predicts multiple cognitive and motor outcome measurements on a personalized level recorded from one learned composite score. This personalized composite score is derived from a large set of multi-modal components from the TREND cohort, including genetic, biofluid, clinical, demographic, and lifestyle factors. We found that a model based on a single composite score was able to predict cognitive and motor abilities almost as well as a classical flexible regression model specifically trained for each single clinical score. In contrast to the flexible regression model, our composite score model is able to identify factors that globally influence cognitive and motoric abilities as measured by multiple clinical scores. The model identified several risk and protective factors for healthy aging and recovered physical exercise as a major, modifiable, protective factor. We conclude that our low parametric modeling approach successfully recovered known risk and protective factors of healthy aging on a personalized level while providing an interpretable composite score. We suggest validating this modeling approach in other cohorts.

Social isolation and likelihood of becoming centenarians: evidence from the Chinese longitudinal healthy longevity survey

BackgroundSocial isolation, defined as an individual’s lack of social connections, is particularly prevalent among older adults. However, its association with health outcomes among the oldest-old population (aged 80 and above) was understudied.AimsTo examine the association between social isolation and the likelihood of becoming a centenarian among the oldest-old people in China, aiming to provide novel insights into promoting healthy aging and longevity.MethodsUsing data from The Chinese Longitudinal Healthy Longevity Survey, conducted in 22 provinces in mainland China since 1998, we performed a community-based, prospective nested case-control study. The primary outcome was survival to the age of 100 by 2018 (the end of follow-up). Information on social isolation and other covariates was collected via a questionnaire at baseline. The degree of social isolation was categorized as low, moderate, and high. Included (n = 5,716) were 1,584 identified centenarians and 4,132 controls (deceased before reaching 100 years), matched by age, sex, and year of entry. A conditional logistic regression model was used to evaluate the association between social isolation and the likelihood of becoming a centenarian, adjusting for demographic factors, lifestyle factors, chronic disease, potential disability, optimistic attitude, and perceived loneliness.ResultsIndividuals with the highest social isolation score had lower odds of becoming centenarians (adjusted OR:0.82; 95% CI: 0.68, 0.98), relative to those with the least social isolation (P-value < 0.05), and this association persisted in sensitivity analyses. The association was more pronounced among ever smokers, compared to never smokers (P-value = 0.001). We did not observe significant interactions between social isolation and other covariates (P-value > 0.05 for all).ConclusionsThis study highlights the inverse association between social isolation and the likelihood of becoming a centenarian, emphasizing the need for public health initiatives to combat isolation in the older population.

Association of oxidative balance score with all-cause mortality among individuals with chronic kidney disease: a cohort study

BackgroundThe Oxidative Balance Score (OBS) is employed for evaluating the body’s overall level of oxidative stress. This study aimed to investigate the association between OBS and mortality in individuals with chronic kidney disease (CKD) using a cohort study design.MethodsWe used data from adult participants(≥ 20 years old) in the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018. CKD is diagnosed based on the Kidney Disease Improving Global Outcomes (KDIGO) guidelines. OBS, which consists of 16 dietary factors and 4 lifestyle factors, categorized into pro-oxidants and antioxidants, with a total score range of 0 to 40 .The OBS was divided into four quartiles (Q1 to Q4), with Q1 (5–12), Q2 (13–18), Q3 (19–24), and Q4 (25–36). We excluded patients with missing data on OBS, CKD, and key covariates.Cox regression analysis were used to examine the relationship between OBS and all-cause mortality in CKD patients. Sensitivity analyses included subgroup analysis and multiple imputation.ResultsWe included a total of 3,984 patients with CKD. During an average follow-up period of 103 months, 1,263 cases (31.7%) of all-cause mortality were recorded. In the fully adjusted model, compared to Q1 the hazard ratios (HRs) and 95% confidence intervals (CIs) for Q4 were as follows: OBS 0.80 (0.68, 0.95) (p = 0.012), dietary OBS 0.78 (0.66, 0.92) (p = 0.003), and lifestyle OBS 0.83 (0.70, 0.99) (p = 0.038). Our sensitivity analyses further confirmed the robustness of these results.ConclusionsHigher OBS was negatively correlated with all-cause mortality risk in American adults with CKD.

African American Females are More Vulnerable to Develop Biliary Injury in NAFLD (Nonalcoholic fatty liver disease) Patients – A Single Institute Experience

Abstract Introduction/Objective Chronic alcohol exposure alone may take decades to induce severe liver disease, yet when combined with elements such as the Western diet, liver pathogenesis accelerates, resulting in earlier symptoms. Identifying the specific contributions of alcohol, diet, and other factors to liver disease is challenging, despite the availability of diagnostic tools like patient histories, liver enzyme tests, imaging, and biopsies. Methods/Case Report This study seeks to detail the liver disease profile of patients who underwent liver biopsies in 2022. Comprehensive profiles were created by retrieving liver biopsy specimens and associated diagnostic data from electronic medical records. Two independent pathologists analyzed the biopsy slides, looking for liver damage associated with alcohol consumption and Western diet influences. We employed enhanced staining techniques to better associate specific types of liver damage with demographic variables. The data analysis was conducted using GraphPad Prism 9 for robust statistical evaluation. Results (if a Case Study enter NA) The research included 88 participants—41 males and 47 females, with average ages of 56 and 62 respectively. The predominant diagnosis was fatty liver disease, with non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) accounting for 26% of cases, and alcoholic liver disease (ALD) making up 10%. The NAFLD/NASH group (n=23) consisted mainly of African Americans (n=15) and Caucasians (n=8). Among these, African Americans showed a significantly greater ductular reaction and portal inflammation (p&amp;lt;0.05). Conversely, no notable differences in portal fibrosis and bile stasis were observed between these groups. Notably, African American females (n=11) demonstrated more severe pathological features compared to Caucasian females (n=6), including elevated levels of ductular reaction, fibrosis, portal inflammation, and bile stasis (p&amp;lt;0.05), suggesting a higher vulnerability to biliary injuries. Conclusion The study highlights the complex interplay between lifestyle factors and liver disease development and emphasizes the need for precise diagnostic strategies that consider these multifactorial influences. Additionally, it reveals ethnic disparities in the pathology of NAFLD, advocating for further research into their causes and implications for clinical management. Future investigations should focus on race and gender-specific factors and adapt local healthcare strategies to effectively manage the escalating burden of liver disease.

Deaths from asthma: a series of cases and their presentations, and the impact on local and global health

Abstract Introduction/Objective Asthma is a lung disease usually characterized by chronic inflammation that affects at least 300 million people globally at all life stages. Asthma is defined by respiratory symptoms such as coughing, wheezing, shortness of breath, and chest tightness with expiratory airflow limitation.The prevalence of asthma is increasing worldwide. Asthma is often under-diagnosed and under-treated, particularly in low- and middle-income countries. Severe disease can result in reduced quality of life or even premature death. Epidemiologic studies are being utilized to compare international incidences of asthma between populations so that etiologic mechanisms involved in the development of asthma can be discovered through research. Asthma prevalence studies require large numbers and high response rates amongst a random population to establish prevalence and severity with reasonable precision. Despite advances in treatments, guidelines, and preventable factors, deaths from asthma account for 250,000 premature deaths each year. Pathology has a key role in asthma identification through examination endobronchial biopsies and whole lung postmortem examination Methods/Case Report We present a series of asthma deaths with variable clinical presentations and histopathologic findings. The postmortem gross and histologic findings highlight the varying severities that asthma can have on the lungs. Knowledge of the clinical symptom presentations, identification of gross findings, appropriate sampling of lung tissue, identification of microscopic acute and chronic features help identify asthma related changes. Understanding common lifestyle, environmental, genetic, and medical care factors that serve as asthma triggers and their role in the onset or continuation of an acute exacerbation will allow for accurate determination of cause, contributing cause, and manner of death. This information, listed on the death certificate, is what helps correlate asthma prevalence with mortality allowing for appropriate allocation of funds for research, prevention and treatment. Results (if a Case Study enter NA) EP abstract Conclusion Outlined are the impacts that asthma can have on individuals, communities, and health systems globally but also ways to identify when death may be or is likely the result of asthma. While asthma cannot be cured, measuring the prevalence of disease and accurately determining asthma as the cause or contributing cause of death can help raise awareness and mitigate the consequences of severe disease.

Challenge of cardiovascular prevention in primary care: achievement of lifestyle, blood pressure, lipids and diabetes targets for primary prevention in England – results from ASPIRE-3-PREVENT cross-sectional survey

BackgroundImplementation of the cardiovascular disease (CVD) prevention guidelines in the UK has been repeatedly evaluated under the auspices of the British Cardiovascular Society in three Action on Secondary and Primary...

Association of modifiable risk factors and infectious diseases among individuals with hypertension: a prospective cohort study

BackgroundA comprehensive assessment of combined modifiable risk factors in relation to infectious diseases among individuals with hypertension is lacking, and the potential mechanisms of these associations remain unclear. To investigate the prospective associations of a combination of lifestyle behaviors and cardiometabolic factors with the risk of infectious diseases among individuals with hypertension and to estimate whether and to what extent blood biomarkers mediate these associations.MethodsThis cohort study included 147,188 participants with hypertension and complete data on modifiable risk factors from the UK Biobank. Health score was constructed from eight modifiable risk factors, including four lifestyle behaviors (diet, physical activity, smoking, and sleep duration) and four cardiometabolic factors (body mass index, blood lipids, blood glucose, and blood pressure). Cox proportional hazards regression analysis was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the health score and infectious diseases. The mediation analysis was performed to assess the potential intermediation effects of blood biomarkers.ResultsOver a median follow-up of 12.5 years, 27,398 participants with infectious diseases were documented, with 960 respiratory infectious diseases and 7940 digestive infectious diseases. After adjusting for potential confounders, the HR (95% CI) for the highest versus the lowest quartile of health score was 0.64 (0.62, 0.66) for infectious diseases, 0.72 (0.60, 0.86) for respiratory infectious diseases, and 0.66 (0.62, 0.71) for digestive infectious diseases. Stratified factors including duration of hypertension did not modify the associations between the health score and infectious diseases. In addition, biomarkers including inflammation and renal function collectively explained 46.60% of the associations between the combined lifestyle factors and infectious disease risk among individuals with hypertension.Conclusions and relevanceIdeal management of combined modifiable risk factors was associated with lower risks of infectious diseases and might produce profound changes in blood biomarkers among individuals with hypertension. Additionally, specific biomarkers appeared to serve as an intermediate between combined lifestyle factors and infectious diseases. These insights highlighted the important role of a combination of healthy lifestyle and favorable cardiometabolic status in reducing disease burden and facilitated the understanding of biological mechanisms underlying modifiable risk factors with infectious diseases.

Integrating lifestyle modifications with physiotherapy: Evaluating the role of nutrition and psychological interventions in recovery

Physiotherapy is widely recognized for its role in rehabilitating musculoskeletal and chronic conditions through physical interventions. However, emerging evidence highlights the importance of lifestyle modifications, particularly dietary changes and psychological support, in enhancing treatment outcomes. This review evaluates the influence of such modifications on the effectiveness of physiotherapy interventions. By synthesizing literature on the integration of nutritional strategies, such as increased intake of anti-inflammatory nutrients, and psychological interventions like cognitive-behavioral therapy (CBT) and mindfulness, the study examines their impact on recovery rates, pain levels, and overall treatment success. Results indicate that dietary changes, including omega-3 fatty acids and antioxidants, promote tissue repair and reduce inflammation, while psychological support improves pain management, patient adherence, and functional recovery. The findings suggest that a holistic approach, incorporating both dietary and psychological elements into physiotherapy, can optimize patient outcomes. Future research should focus on standardized protocols to integrate these lifestyle factors with physiotherapy for sustained rehabilitation success.

Impact of concomitant prescriptions and lifestyle factors on the initial course of newly diagnosed inflammatory bowel disease

Introduction: There is a close relationship between the relapse of inflammatory bowel disease (IBD) and lifestyle factors, including concomitant medications such as non-steroidal anti-inflammatory drugs (NSAIDs), antithrombotic drugs, smoking status, and alcohol consumption. However, solid evidence is limited regarding the risk factors at diagnosis and initial disease course. This study aimed to explore the impact of concomitant prescriptions and lifestyle factors in patients with newly diagnosed IBD using a large-scale real-world database. Methods: This is a retrospective inception cohort study using the insurance claims database. Newly diagnosed patients with UC and CD were enrolled between January 2005 and May 2020. Concomitant prescriptions and lifestyle factors were assessed for new biologics use, surgery, and hospitalization during the first year. Results: In total, 6,743 patients with UC and 1,000 patients with CD were enrolled. Proton pump inhibitors, antithrombotics, antibiotics, and NSAIDs were identified as associated factors for both biologics use and hospitalization in UC patients (all p&amp;lt;0.01), and antithrombotics were identified as associated factors for both biologics use and hospitalization in CD patients (all p&amp;lt;0.01) in multivariable analyses. Interestingly, smoking was protective against hospitalization in UC patients (p&amp;lt;0.01), but not in CD patients (p=0.997), analyzed by univariate analysis. Alcohol consumption was protective against hospitalization outcomes in UC patients (p=0.02) but not in CD patients (p=0.27), analyzed by univariate analysis. Conclusion: Immediate attention should be paid to concomitant medications at diagnosis, because they may have impact on the initial course of IBD.

Exploring the link between sedentary behavior and cognitive decline: a comprehensive study combining Mendelian randomization and animal model experiments.

The causal link between detrimental behaviors and cognitive performance remains unclear. This research seeks to investigate the causal impact of adjustable lifestyle factors on cognitive deterioration, including frequency of alcohol intake, onset of smoking, and sedentary activities like prolonged television viewing. This research combines large-scale genetic data obtained from univariable and multivariable Mendelian randomization analyses with experimental findings obtained from animal models. Our findings reveal that the odds ratio (OR) for cognitive function deterioration was 0.445 (inverse variance weighted [IVW] 95% CI: 0.370 to 0.536, p < 0.001) for each standard deviation increase in television watching time. After adjustment for body mass index (BMI), number of days walked /moderate activity over 10+ min and education in Multivariable Mendelian Randomization (MVMR), only the genetic predisposition to increased television watching time remained significantly associated with worse cognitive function (OR 0.659, 95% CI: 0.452 to 0.960, p = 0.030). The other two habits had no significant effects. Sensitivity analyses have confirmed that genetic pleiotropy did not influence the results. To further explore the relationship between sedentary behavior and cognitive function, as well as the underlying mechanisms, we conducted a restricted cage housing experiment and a physical exercise training experiment in mice. The results showed that physical exercise significantly improved spatial memory, as assessed by the Morris water maze, and increased exploratory interest, as evaluated by the open field test (OFT) and the elevated plus-maze test, compared to the sedentary control group. These cognitive advantages may be mediated through mechanisms involving free radical scavenging and enhanced synaptic plasticity. Our research provides genetic evidence indicating that extended television viewing is linked to an elevated risk of cognitive decline. Additionally, experimental data from mouse models suggest that physical exercise can counteract cognitive decline and anxiety-like behaviors induced by sedentary behavior. This protective effect is likely mediated by reactive oxygen species (ROS)-dependent mechanisms that enhance synaptic plasticity within the hippocampus.

The role of nutrition and gut microbiome in the progression of multiple myeloma and its precursor disease.

Multiple myeloma (MM) is the second most common hematological malignancy, characterized by unregulated monoclonal proliferation in the bone marrow. Monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM) are premalignant conditions that can progress to MM. Identifying etiological risk factors for MM and its precursor diseases is crucial for prevention. Obesity, diet, vitamin D levels, and gut microbiota alterations have been identified as lifestyle factors affecting MM and MGUS risk. Upon disease onset, treatment strategies aim to reduce disease burden, enhance prognosis, and optimize patients' quality of life. Nutrition and body weight have been shown to affect disease progression and treatment outcomes. MM patients often present with vitamin D, vitamin B12, and folate deficiencies, which worsen disease prognosis. High body mass index is linked to increased death rates among MM patients and an increased risk of MGUS transformation to MM. Gut microbiota has also been associated with disease progression and response to treatment. This literature review aims to summarize the available evidence regarding the impact of nutrition and nutritional status on MM patients beyond prevention, highlighting the significance of gut microbiome and dysbiosis in MM progression.

Investigating the Spatial Patterns of Heavy Metals in Topsoil and Asthma in the Western Salt Lake Valley, Utah

Mining activities, particularly in large excavations like the Bingham Canyon Copper Mine in Utah, have been increasingly linked to respiratory conditions due to heavy-metal-enriched waste and dust. Operating continuously since 1906, the Bingham Canyon Copper Mine contributes 4.4% of the Salt Lake Valley PM2.5 pollution. However, the extent of its contributions to larger-sized particulate matter (PM10) dust, soil and water contamination, and human health impacts is largely unknown. Aerosol optical depth data from Sentinel-2 imagery revealed discernible dust clouds downwind of the mine and smelter on non-prevailing-wind days, suggesting potential heavy metal dispersion from this fugitive dust and subsequent deposition to nearby surface soils. Our analysis of topsoils from across the western Salt Lake Valley found mean arsenic, copper, lead, and zinc concentrations to be well above global background concentrations. Also, the minimum values for arsenic and maximum values for lead were well above the US EPA regional screening levels for residential soils. Thus, arsenic is the metal of greatest concern for impacts on human health. Elevated concentrations of all metals were most notable near the mine, smelter, and tailings pond. Our study linked these elevated heavy metal levels to regional asthma outcomes through cluster analysis and distance-related comparison tests. Significant clusters of high asthma rates were observed in regions with elevated topsoil heavy metal concentrations, impacting both low- and high-income neighborhoods. The findings of this preliminary study suggest that the mine, smelter, and recent construction activities, especially on lands reclaimed from former tailings ponds, could be contributing to atmospheric dust containing high levels of heavy metals and exacerbating asthma outcomes for residents. However, the methods used in the study with aggregated health outcome data cannot determine causal links between the heavy metal contents of soil and health outcomes; they can only point to potential links and a need for further investigation. Such further investigation should involve individual-level data and control for potential confounding factors, such as socioeconomic status, access to healthcare, and lifestyle factors, to isolate the effect of metal exposures on asthma outcomes. This study focused on atmospheric deposition as a source of heavy metal enrichment of topsoil. However, future research is also essential to assess levels of heavy metals in subsoil parent materials and local surface and groundwaters to be able to assess the links between the sources or methods of soil contamination and health outcomes.

Geographical variations and predictors of coronary artery disease mortality in Turkiye: an environmental and behavioral analysis

ObjectiveThis study aims to analyze the geographical variations and identify key environmental and behavioral predictors of coronary artery disease (CAD) mortality in Turkiye.MethodsA 10-year longitudinal province-level data was used to identify change trajectories of CAD mortality. Environmental determinants (such as air quality and climatic conditions) and behavioral factors of alcohol consumption and smoking were examined for their association with CAD mortality change trajectories using Ordinal Logistic Regression models.ResultsThe study revealed significantly different trajectoriesof CAD mortality across Turkiye. Environmental factors, particularly air quality (Particulate Matter-10 variation) and climatic conditions (humidity and temperature variations), were heavily associated with the level of CAD mortality. Behavioral factors, notably alcohol consumption and smoking, also exhibited a significantly positive association. Humidity, sunlight, and temperature remained as key predictors of CAD after controlling for smoking and alcohol consumption.ConclusionThe study underscores the importance of addressing environmental and lifestyle factors in CAD management and prevention strategies. The findings suggest the necessity for region-specific interventions and public health policies tailored to the unique characteristics of each province in Turkiye. This research contributes to a deeper understanding of the multifactorial nature of CAD mortality, providing valuable insights for future research to investigate causal associations, healthcare planning, and policy-making.Trial registrationOur study has been registered in ClinicalTrials.GOV system with a procotol ID of CAD001.

A multilayer network analysis of Alzheimer's disease pathogenesis: Roles for p-tau, synaptic peptides, and physical activity.

In the aging brain, cognitive abilities emerge from the coordination of complex pathways arising from a balance between protective lifestyle and environmental factors and accumulation of neuropathologies. As part of the Rush Memory and Aging Project (n=440), we measured accelerometer-based actigraphy, cognitive performance, and after brain autopsy, selected reaction monitoring mass spectrometry. Multilevel network analysis was used to examine the relationships among the molecular machinery of vesicular neurotransmission, Alzheimer's disease (AD) neuropathology, cognition, and late-life physical activity. Synaptic peptides involved in neuronal secretory function were the most influential contributors to the multilayer network, reflecting the complex interdependencies among AD pathology, synaptic processes, and late-life cognition. Older adults with lower physical activity evidenced stronger adverse relationships among phosphorylated tau peptides, markers of synaptic integrity, and tangle pathology. Network-based approaches simultaneously model interdependent biological processes and advance understanding of the role of physical activity in age-associated cognitive impairment. Network-based approaches simultaneously model interdependent biological processes. Secretory synaptic peptides were influential contributors to the multilayer network. Older adults with lower physical activity had adverse relationships among pathology. There was interdependence among phosphorylated tau, synaptic integrity, and tangles. Network methods elucidate the role of physical activity in cognitive impairment.

PREDIKSI PENYAKIT JANTUNG MENGGUNAKAN METODE RANDOM FOREST DAN PENERAPAN PRINCIPAL COMPONENT ANALYSIS (PCA)

Heart disease is a significant public health issue and the leading cause of death worldwide. Risk factors such as hypertension, diabetes, obesity, sedentary lifestyle, smoking, and genetic factors contribute to the development of heart disease. This study aims to develop a heart disease prediction model using the Random Forest method. The dataset used comes from the UCI Machine Learning Repository, containing data from 1026 patients with various health features. The methods used include the stages of knowledge discovery in databases (KDD), namely data selection, preprocessing, transformation, data mining, and evaluation. The study results show that the model with 100 decision trees achieved an accuracy of 0.9823. Further evaluation using the confusion matrix and classification report indicates that the Random Forest method provides 98% accuracy, 100% precision, 96% recall, and a 98% F1-score. In conclusion, the Random Forest method is effective in predicting heart disease, with features such as thal having a significant impact on model accuracy.

Sedentary Lifestyle Is a Modifiable Risk Factor for Cognitive Impairment in Patients on Dialysis and after Kidney Transplantation

Background: Chronic kidney disease (CKD) is a risk factor for cognitive impairment (CI), and this risk is the highest in patients with end-stage kidney disease (ESKD). As a multifactorial disease, CI may be influenced by several potentially modifiable lifestyle and behavioral factors that may reduce or increase the risk of dementia. The aim of this study was to evaluate the associations between the known modifiable risk factors for dementia and the risk of CI in patients with ESKD treated with renal replacement therapy. The Charlson Comorbidity Index and the risk of CI in patients with ESKD were also assessed. Methods: In this cross-sectional study, 225 consecutive patients with ESKD treated with different modalities of renal replacement therapy were assessed for cognitive decline using the Addenbrooke’s Cognitive Examination (ACE III) test. Information was also collected on modifiable risk factors for dementia, medical history and demographics. Results: This study included 117 patients after kidney transplantation (KT) and 108 patients with ESKD undergoing peritoneal dialysis and hemodialysis. The prevalence of modifiable risk factors for dementia differed between the groups; KT patients were more likely to be physically active, residing in cities with populations of less than 500,000 inhabitants, and were less likely to suffer from depression. Furthermore, the KT group had a lower Charlson Comorbidity Index score, indicating less severe comorbidities, and a lower risk of CI (3.6 ± 1.67 vs. 5.43 ± 2.37; p = 0.001). In both the KT and dialysis groups, patients with CI were more likely to have a sedentary lifestyle (45% vs. 9%, p = 0.001 and 88% vs. 48%, p = 0.001, respectively), whereas lower educational attainment and depression had a significant negative impact on ACE III test results, but only in KT patients. Finally, cognitive function in dialysis patients was negatively affected by social isolation and living in urban areas. Conclusions: Modifiable risk factors for dementia, particularly a sedentary lifestyle, are associated with a higher risk of CI in patients treated with different renal replacement therapy modalities. As CI is an irreversible condition, it is important to identify lifestyle-related factors that may lead to dementia in order to improve or maintain cognitive function in patients with ESKD.